Mechanisms, Microenvironments, and Models: Understanding Therapeutic Resistance in Glioblastoma

Glioblastoma (GBM) is the most common and lethal primary malignant brain tumor in adults. Despite aggressive multimodal therapy, including maximal safe resection, radiation therapy, and temozolomide chemotherapy, median survival remains approximately 16 months, and nearly all tumors recur. Over the past 2 decades, numerous therapies that demonstrated promise in preclinical studies have failed to improve outcomes in randomized clinical trials, underscoring the therapeutic resistance that defines this disease. This resistance arises from the convergence of tumor-intrinsic mechanisms, microenvironmental constraints, and limitations of current preclinical models. In this review, we synthesize advances in understanding the molecular, cellular, and anatomic determinants of resistance to radiation therapy, chemotherapy, targeted therapies, and immunotherapies in adult GBM. We highlight how extensive intra- and intertumoral heterogeneity, transcriptional plasticity, and adaptive reprogramming enable tumor cells to evade cytotoxic stress. Key resistance mechanisms include activation of DNA damage response pathways, exploitation of hypoxic niches, therapy-induced mesenchymal transitions, and evasion of immune surveillance through impaired antigen presentation and a profoundly immunosuppressive tumor microenvironment. We further discuss how GBM exploits the unique immunologic features of the central nervous system, including the blood-brain barrier, limited antigen burden, and tolerogenic myeloid populations, to blunt the efficacy of immunotherapies. A major focus of this review is the role of preclinical models in shaping our understanding of therapeutic resistance. We critically evaluate established cell lines, patient-derived xenografts, syngeneic models, and genetically engineered mouse models, emphasizing both their strengths and their inability to fully recapitulate defining features of human GBM. Finally, we outline emerging strategies to overcome resistance, including rational combination therapies, adaptive trial designs, improved biomarker-driven stratification, and integrative modeling approaches. Together, these insights provide a framework for translating mechanistic understanding into more effective, durable therapies for glioblastoma.